Technologies that exploit the endogenous RNA-based gene silencing mechanism, RNA interference (RNAi), have developed rapidly for the dissection of gene-function relationships and as a means of furthering molecular target analysis. However, the gene-specific effects mediated by a particular RNAi effector is difficult to predict and is frequently poorly reported in the literature. We set out to establish robust assays and cell line based model systems to enable rapid and reproducible assessment of the effects of RNAi on gene-specific transcript and protein levels. We initially focused on the assessment of the gene silencing mediated by a population of synthetic siRNAs. We have now fully assessed and optimized for our use a commercial RNA assay (Quantigene, Genopsectra Inc.) that allows us to conduct RNAi analysis at an RNA level in relatively high-throughput. We have now utilized the Quantigene assay to analyze RNAi for over 100 human genes and have also used a Western blot based assay system and an ECL protein analysis method to quantify the knockdown mediated at a protein level for 19 human proteins. The results of this analysis form a key part of a recently published article in Nucleic Acids Research. This data set represents one of the largest of its kind available in the public domain. We have also extended our RNAi analysis to make use of a multiplex version of the Quantigene assay system; initial results are very encouraging. The value of large, high-throughput RNAi screens in human cells has been demonstrated in a number of studies. Critical to developing effective RNAi screening has been the development of suitable high-throughput formats, assays, statistical analysis and down-stream validation procedures. We have conducted several Independent and collaborative studies to establish conditions for RNAi screening in several different cancer cell lines including those used routinely for studies of breast, ovarian, and colorectal cancer. One RNAi screen conducted using a multiplex approach that combined siRNAs to multiple genes so as to compress the size of the screen. This screen, conducted in a breast cancer cell line identified a number of known and putative anti-cancer molecular targets; the results of this study have been published in Nucleic Acids Research. Having developed optimized conditions we have studied a variety of independent and collaborative RNAi screens to identify novel cancer associated genes and including genes that can be exploited directly as anti-cancer molecular targets have now been performed. This hypothesis generating approach has identified a number of proteins that influence the growth of cancer cell lines as a result of our independent and collaborative RNAi screens and follow up analysis to investigate these specific proteins are on going.